69 research outputs found

    CORNETO: A Software System for Simulating and Optimizing Optical Networks

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    In this paper we present a software system that is being developed at the University of Leeds for simulating and optimizing energy efficient optical core networks. The system is called CORNETO, an acronym for CORe NETwork Optimization. The software implements many of the energy saving concepts, methods and computational heuristics that have been produced by the ongoing INTERNET, INTelligent Energy awaRe NETworks, project. The main objective of the software is to help network operators and planners green their networks while maintaining quality of service. In this paper we briefly describe the software and demonstrate its capabilities with two case studies

    Energy Efficient Core Networks with Clouds

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    The popularity of cloud based applications stemming from the high volume of connected mobile devices has led to a huge increase in Internet traffic. In order to enable easy access to cloud applications, infrastructure providers have invested in geographically distributed databases and servers. However, intelligent and energy efficient high capacity transport networks with near ubiquitous connectivity are needed to adequately and sustainably serve these requirements. In this thesis, network virtualisation has been identified as a potential networking paradigm that can contribute to network agility and energy efficiency improvements in core networks with clouds. The work first introduces a new virtual network embedding core network architecture with clouds and a compute and bandwidth resource provisioning mechanism aimed at reducing power consumption in core networks and data centres. Further, quality of service measures in compute and bandwidth resource provisioning such as delay and customer location have been investigated and their impact on energy efficiency established. Data centre location optimisation for energy efficiency in virtual network embedding infrastructure has been investigated by developing a MILP model that selects optimal data centre locations in the core network. The work also introduces an optical OFDM based physical layer in virtual network embedding to optimise power consumption and optical spectrum utilization. In addition, virtual network embedding schemes aimed at profit maximization for cloud infrastructure providers as well greenhouse gas emission reduction in cloud infrastructure networks have been investigated. GreenTouch, a consortium of industrial and academic experts on energy efficiency in ICTs, has adopted the work in this thesis as one of the measures of improving energy efficiency in core networks

    Evaluating the energy consumption and the energy savings potential in ICT backbone networks

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    Energy efficiency of Optical OFDM-based networks

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    Orthogonal Frequency Division Multiplexing (OFDM) has been proposed as an enabling technique for elastic optical networks to support heterogeneous traffic demands. In this paper, we investigate the energy efficiency of rate and modulation adaptive optical OFDM-based networks. A mixed integer linear programming (MILP) model is developed to minimize the total power consumption of optical OFDM networks. We differentiate between two optimization schemes: power-minimized and spectrum-minimized optical OFDM-based networks. The results show that while similar power consumption savings of up to 31% are achieved by the two schemes compared to conventional IP over WDM networks, the spectrum-minimized optical OFDM is 51% more efficient in utilizing the spectrum compared to the power-minimized optical OFD

    Stochastic Energy Efficient Cloud Service Provisioning Deploying Renewable Energy Sources

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    Disaster Resilient Optical Core Networks

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    During the past few years, the number of catastrophic disasters has increased and its impact sometimes incapacitates the infrastructures within a region. The communication network infrastructure is one of the affected systems during these events. Thus, building a resilient network backbone is essential due to the big role of networks during disaster recovery operations. In this thesis, the research efforts in building a disaster-resilient network are reviewed and open issues related to building disaster-resilient networks are discussed. Large size disasters not necessarily impact the communication networks, but instead it can stimulate events that cause network performance degradation. In this regard, two open challenges that arise after disasters are considered one is the short-term capacity exhaustion and the second is the power outage. First, the post-disaster traffic floods phenomena is considered. The impact of the traffic floods on the optical core network performance is studied. Five mitigation approaches are proposed to serve these floods and minimise the incurred blocking. The proposed approaches explore different technologies such as excess or overprovisioned capacity exploitation, traffic filtering, protection paths rerouting, rerouting all traffic and finally using the degrees of freedom offered by differentiated services. The mitigation approaches succeeded in reducing the disaster induced traffic blocking. Second, advance reservation provisioning in an energy-efficient approach is developed. Four scenarios are considered to minimise power consumption. The scenarios exploit the flexibility provided by the sliding-window advance reservation requests. This flexibility is studied through scheduling and rescheduling scenarios. The proposed scenarios succeeded in minimising the consumed power. Third, the sliding-window flexibility is exploited for the objective of minimising network blocking during post-disaster traffic floods. The scheduling and rescheduling scenarios are extended to overcome the capacity exhaustion and improve the network blocking. The proposed schemes minimised the incurred blocking during traffic floods by exploiting sliding window. Fourth, building blackout resilient networks is proposed. The network performance during power outages is evaluated. A remedy approach is suggested for maximising network lifetime during blackouts. The approach attempts to reduce the required backup power supply while minimising network outages due to limited energy production. The results show that the mitigation approach succeeds in keeping the network alive during a blackout while minimising the required backup power

    Energy-Efficient Traffic Scheduling in IP over WDM Networks

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    In this paper, we investigate the energy efficiency that can be achieved by using traffic scheduling in IP over WDM networks. A mixed integer linear programming model is developed to optimize routing and scheduling in dynamically arriving demands, where part of the demands can be allocated within a sliding window. The results show that scheduling improves the energy efficiency of non-bypass IP/WDM networks, with traffic grooming by up to 25% and blocking is reduced by 30%

    Energy-oriented models for WDM networks

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    A realistic energy-oriented model is necessary to formally characterize the energy consumption and the consequent carbon footprint of actual and future high-capacity WDM networks. The energy model describes the energy consumption of the various network elements (NE) and predicts their energy consumption behavior under different traffic loads and for the diverse traffic types, including all optical and electronic traffic, O/E/O conversions, 3R regenerations, add/drop multiplexing, etc. Besides, it has to be scalable and simple to implement, manage and modify according to the new architecture and technologies advancements. In this paper, we discuss the most relevant energy models present in the literature highlighting possible advantages, drawbacks and utilization scenarios in order to provide the research community with an overview over the different energy characterization frameworks that are currently being employed in WDM networks.Peer ReviewedPostprint (author’s final draft

    Heuristic for Lowering Electricity Costs for Routing in Optical Data Center Networks

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    Optical data centers consume a large quantity of energy and the cost of that energy has a significant contribution to the operational cost in data centers. The amount of electricity consumption in data centers and their related costs are increasing day by day. Data centers are geographically distributed all around the continents and the growing numbers of data replicas have made it possible to find more cost effective network routing. Besides flat-rate prices, today, there are companies which offers real-time pricing. In order to address the energy consumption cost problem, we propose an energy efficient routing scheme to find least cost path to the replicas based on real-time pricing model called energy price aware routing (EPAR). Our research considers anycast data transmission model to find the suitable replica as well as the fixed window traffic allocation model for demand request to reduce the energy consumption cost of data center networks
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